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» Discovering Classification from Data of Multiple Sources
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HIS
2004
13 years 9 months ago
K-Ranked Covariance Based Missing Values Estimation for Microarray Data Classification
Microarray data often contains multiple missing genetic expression values that degrade the performance of statistical and machine learning algorithms. This paper presents a K rank...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
CIKM
1994
Springer
13 years 11 months ago
Intelligent Caching: Selecting, Representing, and Reusing Data in an Information Server
Accessing information sources to retrieve data requested by a user can be expensive, especially when dealing with distributed information sources. One way to reduce this cost is t...
Yigal Arens, Craig A. Knoblock
JMLR
2010
161views more  JMLR 2010»
13 years 2 months ago
Accuracy-Rejection Curves (ARCs) for Comparing Classification Methods with a Reject Option
Data extracted from microarrays are now considered an important source of knowledge about various diseases. Several studies based on microarray data and the use of receiver operat...
Malik Sajjad Ahmed Nadeem, Jean-Daniel Zucker, Bla...
ICASSP
2011
IEEE
12 years 11 months ago
A non-negative approach to semi-supervised separation of speech from noise with the use of temporal dynamics
We present a semi-supervised source separation methodology to denoise speech by modeling speech as one source and noise as the other source. We model speech using the recently pro...
Gautham J. Mysore, Paris Smaragdis
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 8 months ago
Knowledge transfer via multiple model local structure mapping
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Jing Gao, Wei Fan, Jing Jiang, Jiawei Han